Undergraduate students
Welcome guide: newly admitted students
Learn moreUpdated CSSE undergraduate guide
Get the detailsUnderstanding your offer of admission
Find out moreMinor in Computer Science guide
See detailsNo booking required! Join us for a meeting!
Note: There will be no academic advising on Tuesday, February 21st
In-person:
- Mon, Tue, Wed 9:30 - 12:00 & 14:00 - 16:30 (ER 10th floor)
Online:
- Mon, Tue 10:00 - 11:00
Meeting URL: https://concordia-ca.zoom.us/s/85840596150
Program information
Undergraduate Calendar — Computer Science Degree Requirements
Basic computer science skills are the perfect complement to any degree program at Concordia. The Minor in Computer Science is designed to meet the growing demand for computer-literate professionals, and may offer students more career opportunities after graduation.
- Section 71.70.5
BCompSc Information & Forms
Honours option available in all Computer Science programs. Students may apply to the Honours program once they have completed 30 credits and have maintained a GPA of 3.00.
See section 71.70.4 of Undergraduate Calendar
This is a one-credit project course set up to meet the special needs of certain students lacking one credit or less for graduation. It is a technical elective. Registration into this course requires the written permission from the Department of Computer Science and Software Engineering.
Students work on a computer science project under the supervision of a faculty member and submit a suitable written report on the work carried out.
Undergraduate Calendar — Software Engineering Degree Requirements
Software Engineering Information & Forms
This is a one-credit project course set up to meet the special needs of certain students lacking one credit or less for graduation. It is a technical elective. Registration into this course requires the written permission from the Department of Computer Science and Software Engineering.
This is a one-credit project course set up to meet the special needs of certain SOEN students lacking one credit or less for graduation. It is a technical elective. Registration into this course requires the written permission from the Department of Computer Science and Software Engineering.
Course specific information
Computer Science
General Electives must be chosen from the following lists*:
Computer Science Electives found in § 71.70.2
Mathematics Electives found in § 71.70.2
General Education Electives found in § 71.110
Basic and Natural Science Course list found in § 71.70.9
Software Engineering
Students must select three General Education elective credits from one of the three approved lists found in § 71.110*. These include Social Sciences, Humanities and Other Complementary Studies.
Extended Credit Program (ECP) or Mature Entry Program (MEP):
Students in the Extended Credit Program (ECP) or the Mature Entry Program (MEP) (see §14.2.3) or any other students who have been assigned credits in Humanities and Social Sciences must select those credits from the Social Sciences and Humanities lists found in § 71.110*. Those credits cannot be chosen from the list of Other Complementary Studies list.
ECP/MEP Elective credits may be chosen from the following lists:
Computer Science Electives found in § 71.70.2 (All three lists)
Basic and Natural Science Course list found in § 71.70.9
Students wishing to take a course not listed in the degree requirements, must receive written permission from the Student Academic Services (SAS) Office of the Gina Cody School of Engineering and Computer Science prior to taking the course.
The contents of this course may vary from offering to offering. See below for course description and availability.
Permission of the Department is generally required.
FALL 2021:
COMP 498 Neuroimage Computing (3 credits) – Section X
Prerequisites: ENGR 371 or COMP233. This course covers concepts, theories and practical knowledge in brain image processing and analysis. A practical introduction of medical imaging principles and image reconstruction will be provided. Topics to be covered include brain atlasing, computational anatomy, radiomics, tractography, image segmentation/classification, deep learning in neuroimaging, image-guided neurosurgery, and computer-assisted diagnosis. State-of-the-art software for neuroimage processing and analysis, as well as popular open source databases will also be covered through assignments and a project. Lectures: 3 hours per week.
WINTER 2023: Not Available
The contents of this course may vary from offering to offering. See below for course description and availability.
Permission of the Department is generally required.
WINTER 2023: Conversational Artificial Intelligence (4 credits)
COMP 499 Deep Learning (4 credits) – Section W
Prerequisite: COMP 432 (machine learning) or permission of the instructor.
This course introduces key concepts related to Conversation AI, covering both theoretical and practical aspects. The lectures will provide a general overview on modern conversational AI systems. The review covers basic machine learning concepts used in Conversational AI, including speech processing techniques. The course will address language models, which are an essential part of modern conversational AI methods. The course also covers higher-level methods such as spoken language understanding and dialogue systems. For each topic addressed during the lecture, a corresponding lab session allows students to familiarize themselves with the practical implementation of the techniques mentioned during the main lecture. The lectures are designed to provide a complete overview of the field of Conversational. A project is required.
Component(s): Lecture 3 hours per week;
Laboratory 2 hours per week
The contents of this course may vary from offering to offering. See below for course description and availability.
Permission of the Department is generally required.
WINTER 2023: Not Available
The contents of this course may vary from offering to offering. See below for course description and availability.
Permission of the Department is generally required.
WINTER 2023: Not Available
Other resources
Course sequences by program
Undergraduate contacts
Undergraduate Program Assistants
Kayla Donovan
ER 1033, Ext. 7915
Natallia Lapko
ER 1035 Ext. 3053
Undergraduate Program Directors
Computer Science
Dr. Tiberiu Popa
ER 1023
Software Engineering
Dr. Tse-Hsun Chen
ER 1244
COOP
Dr. Rajajopalan Jayakumar
ER 903